Some features of our web site require JavaScript to function properly. Please enable JavaScript in your browser.
Position
Postdoctoral Researcher in Geospatial AI & Earth Observation
Employer
KTH Royal Institute of Technology
Since 1827, KTH Royal Institute of Technology, has grown to become an international leading technical university. As the largest institution in Sweden for technical education and research, we bring together students, researchers, and educators worldwide. Our activities are grounded in a strong tradition of advancing science and innovation, focusing on contributing to sustainable societal development.
Homepage: https://www.kth.se
Location
Stockholm, Sweden
Sector
Academic
Relevant divisions
Earth and Space Science Informatics (ESSI)
Hydrological Sciences (HS)
Natural Hazards (NH)
Type
Full time
Level
Entry level
Salary
Open
Required education
PhD
Application deadline
Open until the position is filled
Posted
9 October 2026
Job Description
Postdoctoral Researcher in Geospatial AI & Earth Observation
Location:
KTH Royal Institute of Technology, Stockholm, Sweden
Duration:
2 Years (Full-time position with possibility of extension)
Host Department:
Department of Real Estate and Construction Management & Digital Futures
About The Position
Are you a driven early-career researcher passionate about pushing the boundaries of
AI, Earth Observation, and Spatial Data Science
? Join us at
KTH Royal Institute of Technology
for a 2-year postdoctoral fellowship at the cutting edge of Geospatial AI.
This position offers a unique opportunity to lead methodological breakthroughs in
Physics-Informed Deep Learning, Spatial Foundation Models, and Resource-Efficient (Green) AI
. You will work within a high-impact, intersectoral ecosystem.
Key Responsibilities & Research Directions
Next-Generation Geospatial AI: Research and develop novel spatiotemporal deep learning models to unify dynamic satellite EO archives and high-resolution terrestrial spatial data.
Physics-Informed & Green AI Paradigms: Embed physical constraints and explore resource-efficient training algorithms (e.g., Forward-Forward learning) to overcome computational bottlenecks and reduce carbon footprints.
High-Performance Computing: Train and deploy multi-modal foundation models.
Interdisciplinary Collaboration: Engage with top researchers, data engineers, and urban decision-makers to transform satellite intelligence into real-world societal impact.
What We Are Looking For
Education: A Ph.D. degree (or close to completion) in Geospatial Information Science, Computer Science, Geodesy, Remote Sensing, Data Science, Applied Mathematics, or a related field.
Technical Skills: Strong background in Deep Learning (PyTorch/TensorFlow), GeoAI/Spatial Data Analytics, and multi-modal data fusion.
Bonus Qualifications: Experience with Physics-Informed Neural Networks (PINNs), Green AI algorithms, satellite imagery processing (Copernicus Sentinel data), or high-performance supercomputing environments.
Soft Skills: Excellent track record of scientific publication, problem-solving mindset, and strong collaborative skills in an international context.
What We Offer
Top-Tier Research Environment: A position at KTH—one of Europe’s leading technical universities—embedded within Digital Futures, Sweden’s flagship research center for digital transformation.
State-of-the-Art Resources: Full access to national GPU supercomputing clusters (NAISS) and cutting-edge geospatial datasets.
Career Development: Ample funding for international conferences, workshops, and networking, designed to establish your academic independence and leadership.
Future Prospects: Fixed 2-year contract with the potential for extension based on performance and ongoing research funding.
Excellent Living Standards: Competitive Swedish post-doc salary, full social security benefits, paid parental leave, healthcare, and high quality of life in Stockholm.
How To Apply
Interested candidates should submit:
Cover letter detailing research interests and motivation.
Curriculum Vitae (CV) including a full list of publications.
Brief research statement outlining relevant expertise.
Contact information for two academic references.
Contact: Dr. Jingbin Liu, Email:
[email protected]
Equal Opportunity Employer:
KTH is committed to gender equality and diversity. We encourage applications from underrepresented groups in technical disciplines.
Go back